Inter-pregnancy interval and risk of recurrent pre-eclampsia: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Women with a history of pre-eclampsia have a higher risk of developing pre-eclampsia in subsequent pregnancies. However, the role of the inter-pregnancy interval on this association is unclear. OBJECTIVE: To explore the effect of inter-pregnancy interval on the risk of recurrent pre-eclampsia or eclampia. SEARCH STRATEGY: MEDLINE, EMBASE and LILACS were searched (inception to July 2015). SELECTION CRITERIA: Cohort studies assessing the risk of recurrent pre-eclampsia in the immediate subsequent pregnancy according to different birth intervals. DATA COLLECTION AND ANALYSIS: Two reviewers independently performed screening, data extraction, methodological and quality assessment. Meta-analysis of adjusted odds ratios (aOR) with 95 % confidence intervals (CI) was used to measure the association between various interval lengths and recurrent pre-eclampsia or eclampsia. MAIN RESULTS: We identified 1769 articles and finally included four studies with a total of 77,561 women. The meta-analysis of two studies showed that compared to inter-pregnancy intervals of 2-4 years, the aOR for recurrent pre-eclampsia was 1.01 [95 % CI 0.95 to 1.07, I(2) 0 %] with intervals of less than 2 years and 1.10 [95 % CI 1.02 to 1.19, I(2) 0 %] with intervals longer than 4 years. CONCLUSION: Compared to inter-pregnancy intervals of 2 to 4 years, shorter intervals are not associated with an increased risk of recurrent pre-eclampsia but longer intervals appear to increase the risk. The results of this review should be interpreted with caution as included studies are observational and thus subject to possible confounding factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".